Image data captured by an image sensor is often initially processed as part of an image processing pipeline in order to prepare the captured image data for further processing or consumption. In this way, real-time corrections or enhancements can be made without consuming other system resources. For example, raw image data may be corrected, filtered, or otherwise modified to provide subsequent components, such as a video encoder, with appropriately scaled image data for encoding and subsequent display, reducing a number of subsequent operations to be performed on the image data at the video encoder.
In order to implement these corrections or enhancements for captured image data, various different devices, components, units, or other modules may be used to implement the varying operations performed as part of an image processing pipeline. An image signal processor, for instance, may include multiple different units or stages at which different image modifications or enhancements can be made to image data obtained from an image sensor. Image processing systems may include systems for machine vision, which provides automated analysis and inspection functionality for images detected by an image sensor module. Machine vision algorithms may identify points of interest (sometimes referred to as keypoints) in an image that facilitate the identification and/or tracking of objects in one or more images. Given the computationally intensive nature of machine vision algorithms, a more efficient implementation of these systems is desirable.